A sparsity-based simplification method for segmentation of spectral-domain optical coherence tomography images

Optical coherence tomography (OCT) has emerged as a promising image modality to characterize biological tissues. With axio-lateral resolutions at the micron-level, OCT images provide detailed morphological information and enable applications such as optical biopsy and virtual histology for clinical needs. Image enhancement is typically required for morphological segmentation, to improve boundary localization, rather than enrich detailed tissue information. We propose to formulate image enhancement as an image simplification task such that tissue layers are smoothed while contours are enhanced. For this purpose, we exploit a Total Variation sparsity-based image reconstruction, inspired by the Compressed Sensing (CS) theory, but specialized for images with structures arranged in layers. We demonstrate the potential of our approach on OCT human heart and retinal images for layers segmentation. We also compare our image enhancement capabilities to the state-of-the-art denoising techniques

KDEL receptors assist dengue virus exit from the endoplasmic reticulum

Membrane receptors at the surface of target cells are key host factors for virion entry; however, it is unknown whether trafficking and secretion of progeny virus requires host intracellular receptors. In this study, we demonstrate that dengue virus (DENV) interacts with KDEL receptors (KDELR), which cycle between the ER and Golgi apparatus, for vesicular transport from ER to Golgi. Depletion of KDELR by siRNA reduced egress of both DENV progeny and recombinant subviral particles (RSPs). Coimmunoprecipitation of KDELR with dengue structural protein prM required three positively charged residues at the N terminus, whose mutation disrupted protein interaction and inhibited RSP transport from the ER to the Golgi. Finally, siRNA depletion of class II Arfs, which results in KDELR accumulation in the Golgi, phenocopied results obtained with mutagenized prME and KDELR knockdown. Our results have uncovered a function for KDELR as an internal receptor involved in DENV trafficking.published_or_final_versio

Cellular and Behavioral Effects of Cranial Irradiation of the Subventricular Zone in Adult Mice

Background: In mammals, new neurons are added to the olfactory bulb (OB) throughout life. Most of these new neurons, granule and periglomerular cells originate from the subventricular zone (SVZ) lining the lateral ventricles and migrate via the rostral migratory stream toward the OB. Thousands of new neurons appear each day, but the function of this ongoing neurogenesis remains unclear. Methodology/Principal Findings: In this study, we irradiated adult mice to impair constitutive OB neurogenesis, and explored the functional impacts of this irradiation on the sense of smell. We found that focal irradiation of the SVZ greatly decreased the rate of production of new OB neurons, leaving other brain areas intact. This effect persisted for up to seven months after exposure to 15 Gray. Despite this robust impairment, the thresholds for detecting pure odorant molecules and short-term olfactory memory were not affected by irradiation. Similarly, the ability to distinguish between odorant molecules and the odorant-guided social behavior of irradiated mice were not affected by the decrease in the number of new neurons. Only long-term olfactory memory was found to be sensitive to SVZ irradiation. Conclusion/Significance: These findings suggest that the continuous production of adult-generated neurons is involved i

Evaluation of methods for detection of fluorescence labeled subcellular objects in microscope images

<p>Abstract</p> <p>Background</p> <p>Several algorithms have been proposed for detecting fluorescently labeled subcellular objects in microscope images. Many of these algorithms have been designed for specific tasks and validated with limited image data. But despite the potential of using extensive comparisons between algorithms to provide useful information to guide method selection and thus more accurate results, relatively few studies have been performed.</p> <p>Results</p> <p>To better understand algorithm performance under different conditions, we have carried out a comparative study including eleven spot detection or segmentation algorithms from various application fields. We used microscope images from well plate experiments with a human osteosarcoma cell line and frames from image stacks of yeast cells in different focal planes. These experimentally derived images permit a comparison of method performance in realistic situations where the number of objects varies within image set. We also used simulated microscope images in order to compare the methods and validate them against a ground truth reference result. Our study finds major differences in the performance of different algorithms, in terms of both object counts and segmentation accuracies.</p> <p>Conclusions</p> <p>These results suggest that the selection of detection algorithms for image based screens should be done carefully and take into account different conditions, such as the possibility of acquiring empty images or images with very few spots. Our inclusion of methods that have not been used before in this context broadens the set of available detection methods and compares them against the current state-of-the-art methods for subcellular particle detection.</p

Fast Retinal Vessel Detection and Measurement Using Wavelets and Edge Location Refinement

The relationship between changes in retinal vessel morphology and the onset and progression of diseases such as diabetes, hypertension and retinopathy of prematurity (ROP) has been the subject of several large scale clinical studies. However, the difficulty of quantifying changes in retinal vessels in a sufficiently fast, accurate and repeatable manner has restricted the application of the insights gleaned from these studies to clinical practice. This paper presents a novel algorithm for the efficient detection and measurement of retinal vessels, which is general enough that it can be applied to both low and high resolution fundus photographs and fluorescein angiograms upon the adjustment of only a few intuitive parameters. Firstly, we describe the simple vessel segmentation strategy, formulated in the language of wavelets, that is used for fast vessel detection. When validated using a publicly available database of retinal images, this segmentation achieves a true positive rate of 70.27%, false positive rate of 2.83%, and accuracy score of 0.9371. Vessel edges are then more precisely localised using image profiles computed perpendicularly across a spline fit of each detected vessel centreline, so that both local and global changes in vessel diameter can be readily quantified. Using a second image database, we show that the diameters output by our algorithm display good agreement with the manual measurements made by three independent observers. We conclude that the improved speed and generality offered by our algorithm are achieved without sacrificing accuracy. The algorithm is implemented in MATLAB along with a graphical user interface, and we have made the source code freely available

Detecting and quantifying stress granules in tissues of multicellular organisms with the Obj.MPP analysis tool

International audienceStress Granules (SGs) are macromolecular assemblies induced by stress and composed of proteins and mRNAs stalled in translation initiation. SGs play an important role in the response to stress and in the modulation of signaling pathways. Furthermore, these structures are related to the pathological ribonucleoprotein (RNP) aggregates found in neurodegenerative disease contexts, highlighting the need to understand how they are formed and recycled in normal and pathological contexts. Although genetically tractable multicellular organisms have been key in identifying modifiers of RNP aggregate toxicity, in vivo analysis of SG properties and regulation has lagged behind, largely due to the difficulty of detecting SG from images of intact tissues. Here, we describe the object detector software Obj.MPP and show how it overcomes the limits of classical object analyzers to extract the properties of SGs from wide-field and confocal images of respectively C. elegans and Drosophila tissues. We demonstrate that Obj.MPP enables the identification of genes modulating the assembly of endogenous and pathological SGs, and thus that it will be useful in the context of future genetic screens and in vivo studies. This article is protected by copyright. All rights reserved

A Protocol to Quantify Cellular Morphodynamics: From Cell Labelling to Automatic Image Analysis

Overview of the First Eukaryome Congress at Insitut Pasteur. Paris, October 16–18, 2019.International audienceCellular morphodynamics can be used as markers for many physiological and pathological processes. This protocol provides a step-by-step guide to identify variations in motility and morphology within (or across) cell populations using non-invasive live imaging and reproducible image analysis techniques such as segmentation and tracking. Detailed instructions cover all the way from cell culturing and labelling to automatic image and statistical analyses, including the definition of multiple descriptors that characterise the shape and movement of cells in a quantitative manner. All methods are available as free open-source software and illustrated by video tutorials